Exploring Deep Learning Neural Networks And Their Applications
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Exploring Deep Learning Neural Networks And Their Applications
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Author : Renata Sloane
language : en
Publisher: Independently Published
Release Date : 2025-04-19
Exploring Deep Learning Neural Networks And Their Applications written by Renata Sloane and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-19 with Computers categories.
Exploring Deep Learning: Neural Networks and Their Applications is the perfect beginner's guide to understanding the powerful world of deep learning and how it's revolutionizing industries. Whether you're new to the field or looking to deepen your knowledge, this book takes you step-by-step through the core concepts of neural networks and their transformative applications in areas like image recognition, natural language processing, and more. Deep learning, a subset of machine learning, has become essential in solving complex problems that traditional models struggle with. With clear, accessible explanations and hands-on examples, this book covers everything from the basics of neural networks to advanced architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs). You'll explore how these networks work, how they learn from data, and how to apply them to real-world problems. Dive into practical applications, such as automated image tagging, sentiment analysis, and language translation, and learn how deep learning models are reshaping fields such as healthcare, finance, and entertainment. With Python and popular deep learning frameworks like TensorFlow and Keras, you'll have the tools to start building your own neural network models. By the end of this book, you'll have a solid understanding of deep learning and the skills to apply neural networks to a variety of challenging and exciting problems.
The Deep Learning Architect S Handbook
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Author : Ee Kin Chin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-29
The Deep Learning Architect S Handbook written by Ee Kin Chin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.
Harness the power of deep learning to drive productivity and efficiency using this practical guide covering techniques and best practices for the entire deep learning life cycle Key Features Interpret your models’ decision-making process, ensuring transparency and trust in your AI-powered solutions Gain hands-on experience in every step of the deep learning life cycle Explore case studies and solutions for deploying DL models while addressing scalability, data drift, and ethical considerations Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDeep learning enables previously unattainable feats in automation, but extracting real-world business value from it is a daunting task. This book will teach you how to build complex deep learning models and gain intuition for structuring your data to accomplish your deep learning objectives. This deep learning book explores every aspect of the deep learning life cycle, from planning and data preparation to model deployment and governance, using real-world scenarios that will take you through creating, deploying, and managing advanced solutions. You’ll also learn how to work with image, audio, text, and video data using deep learning architectures, as well as optimize and evaluate your deep learning models objectively to address issues such as bias, fairness, adversarial attacks, and model transparency. As you progress, you’ll harness the power of AI platforms to streamline the deep learning life cycle and leverage Python libraries and frameworks such as PyTorch, ONNX, Catalyst, MLFlow, Captum, Nvidia Triton, Prometheus, and Grafana to execute efficient deep learning architectures, optimize model performance, and streamline the deployment processes. You’ll also discover the transformative potential of large language models (LLMs) for a wide array of applications. By the end of this book, you'll have mastered deep learning techniques to unlock its full potential for your endeavors.What you will learn Use neural architecture search (NAS) to automate the design of artificial neural networks (ANNs) Implement recurrent neural networks (RNNs), convolutional neural networks (CNNs), BERT, transformers, and more to build your model Deal with multi-modal data drift in a production environment Evaluate the quality and bias of your models Explore techniques to protect your model from adversarial attacks Get to grips with deploying a model with DataRobot AutoML Who this book is for This book is for deep learning practitioners, data scientists, and machine learning developers who want to explore deep learning architectures to solve complex business problems. Professionals in the broader deep learning and AI space will also benefit from the insights provided, applicable across a variety of business use cases. Working knowledge of Python programming and a basic understanding of deep learning techniques is needed to get started with this book.
International Conference On Emerging Applications And Technologies For Industry 4 0 Eati 2020
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Author : Jemal H. Abawajy
language : en
Publisher: Springer Nature
Release Date : 2021-07-14
International Conference On Emerging Applications And Technologies For Industry 4 0 Eati 2020 written by Jemal H. Abawajy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-14 with Technology & Engineering categories.
This book addresses the adoption of intelligent algorithms for resolving challenges in different aspects of the society such as sport, cyber-security, COVID-19 pandemic, advertising, driving, smart environment—sensors, blockchain, cloud computing, and health. In addition, the book also covers machine learning fundamentals such as feature selection. The book presents practical simulation results and different illustrations in different chapters for easy understanding of concepts and approaches. The types of contributions in the book are as follows: original research, survey, and theoretical insight that describe advancement in the adoption of technique for resolving the broad range of challenges. Researchers, undergraduates, postgraduates, and industry experts will find the book as a valuable resource that bridges theory and practice.
Proceedings Of The International Field Exploration And Development Conference 2022
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Author : Jia'en Lin
language : en
Publisher: Springer Nature
Release Date : 2023-08-05
Proceedings Of The International Field Exploration And Development Conference 2022 written by Jia'en Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-05 with Science categories.
This book focuses on reservoir surveillance and management, reservoir evaluation and dynamic description, reservoir production stimulation and EOR, ultra-tight reservoir, unconventional oil and gas resources technology, oil and gas well production testing, and geomechanics. This book is a compilation of selected papers from the 12th International Field Exploration and Development Conference (IFEDC 2022). The conference not only provides a platform to exchanges experience, but also promotes the development of scientific research in oil & gas exploration and production. The main audience for the work includes reservoir engineer, geological engineer, enterprise managers, senior engineers as well as professional students.
Deep Learning Applications
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Author : M. Arif Wani
language : en
Publisher: Springer Nature
Release Date : 2020-02-28
Deep Learning Applications written by M. Arif Wani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-28 with Technology & Engineering categories.
This book presents a compilation of selected papers from the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2018), focusing on use of deep learning technology in application like game playing, medical applications, video analytics, regression/classification, object detection/recognition and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
Exploring Machine Learning Theory Practice And Innovations
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Author : Dr. Vanitha Kakollu
language : en
Publisher: Academic Guru Publishing House
Release Date : 2024-12-23
Exploring Machine Learning Theory Practice And Innovations written by Dr. Vanitha Kakollu and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-23 with Study Aids categories.
“Exploring Machine Learning: Theory, Practice, and Innovations” is a thoughtfully curated resource that bridges the gap between foundational concepts and advanced methodologies in machine learning. With its systematic structure and practical orientation, the book caters to both beginners and experienced professionals in the field. The content is meticulously organised to align with the learner’s journey in understanding machine learning. The first chapter lays the groundwork by distinguishing human learning from machine learning, elucidating key concepts, and highlighting the potential and limitations of machine learning applications. A dedicated section on data preparation ensures readers grasp the significance of data preprocessing, quality enhancement, and exploration, setting the stage for successful modeling. The book’s core chapters address model selection, training, evaluation, and optimisation while introducing pivotal feature engineering techniques. Readers are guided through Bayes’ Theorem and its role in concept learning, followed by an exploration of supervised and unsupervised learning methods. Advanced algorithms, including decision trees, neural networks, and clustering techniques, are explained with clarity and context. Deep learning and neural networks are given special attention, with a focus on architecture, activation functions, and learning processes. The inclusion of contemporary topics such as ensemble learning and regularisation highlights the text’s relevance in modern machine learning landscapes. Practical insights are enriched by case studies across diverse applications, showcasing how theory translates into innovation. “Exploring Machine Learning” serves as a comprehensive, accessible, and indispensable guide for navigating the dynamic world of machine learning.
Proceedings Of The International Field Exploration And Development Conference 2024
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Author : Jia'en Lin
language : en
Publisher: Springer Nature
Release Date : 2025-07-07
Proceedings Of The International Field Exploration And Development Conference 2024 written by Jia'en Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-07 with Technology & Engineering categories.
This book compiles selected papers from the 14th International Field Exploration and Development Conference (IFEDC 2024). The work focuses on topics including Reservoir Exploration, Reservoir Drilling & Completion, Field Geophysics, Well Logging, Petroliferous Basin Evaluation, Oil & Gas Accumulation, Fine Reservoir Description, Complex Reservoir Dynamics and Analysis, Low Permeability/Tight Oil & Gas Reservoirs, Shale Oil & Gas, Fracture-Vuggy Reservoirs, Enhanced Oil Recovery in Mature Oil Fields, Enhanced Oil Recovery for Heavy Oil Reservoirs, Big Data and Artificial Intelligence, Formation Mechanisms and Prediction of Deep Carbonate Reservoirs, and other Unconventional Resources. The conference serves as a platform not only for exchanging experiences but also for advancing scientific research in oil & gas exploration and production. The primary audience for this work includes reservoir engineers, geological engineers, senior engineers, enterprise managers, and students.
Exploring Youth Studies In The Age Of Ai
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Author : Zaremohzzabieh, Zeinab
language : en
Publisher: IGI Global
Release Date : 2024-07-24
Exploring Youth Studies In The Age Of Ai written by Zaremohzzabieh, Zeinab and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.
In an era defined by the relentless march of technology, the seamless integration of Artificial Intelligence (AI) into our daily lives has ushered in a transformative landscape. At the forefront of this evolution are the Digital Natives of Generation AI, navigating the complexities of a digital world where algorithms are integral to their daily experiences. This juncture presents a dual influence, marked by the continuous progression of technological advancements and the dynamic ways the youngest members of our society engage with and adapt to the digital environment. As we stand at the crossroads of youth studies and AI, there arises a pressing need to comprehend the profound impact of this convergence on the future leaders of our world. Addressing this imperative, Exploring Youth Studies in the Age of AI emerges as a comprehensive solution to unravel the complexities and opportunities within this evolving landscape. This book, meticulously crafted for academics, researchers, educators, policymakers, and technology ethicists, serves as a guiding beacon in understanding how AI shapes the experiences of today's youth and, in turn, how youth culture influences the development and application of AI technologies. With a collection of enlightening chapters covering topics from "Data-Driven Pedagogies" to "Ethical AI: Guiding Principles for Youth-Centric Development," the book delves deep into the diverse dimensions of this intersection, providing actionable insights and fostering a nuanced understanding for those invested in the ethical, social, and educational implications of AI within the context of youth.
Neurorobotics Explores Machine Learning
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Author : Fei Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-20
Neurorobotics Explores Machine Learning written by Fei Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Science categories.
Deep Learning For Nlp And Speech Recognition
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.